Are Loss Functions All the Same?

  title={Are Loss Functions All the Same?},
  author={Lorenzo Rosasco and Ernesto de Vito and Andrea Caponnetto and Michele Piana and Alessandro Verri},
  journal={Neural Computation},
In this letter, we investigate the impact of choosing different loss functions from the viewpoint of statistical learning theory. We introduce a convexity assumption, which is met by all loss functions commonly used in the literature, and study how the bound on the estimation error changes with the loss. We also derive a general result on the minimizer of the expected risk for a convex loss function in the case of classification. The main outcome of our analysis is that for classification, the… 

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